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  • Data Science, Machine Learning and AI

  • DEVOPS

  • CLOUD COMPUTING

  • SOFTWARE DEVELOPMENT AND TESTING

  • IT SERVICE AND PROJECT MANAGEMENT

  • MOBILE & WEB DEVELOPMENT

  • CYBER SECURITY, NETWORKING & BLOCK CHAIN

  • DATABASES & BIG DATA

  • BUSINESS INTELLIGENCE

  • WINDOWS & VIRTUALIZATION

  • TESTING

Deep Learning with Python Training Course Overview

What is Python Deep Learning Course about? Learn to implement Keras on top of TensorFlow to experiment with deep neural networks and tune machine learning models to produce more successful results with this course. Work on different types of Deep Architectures: Convolutional Networks, Recurrent Networks, and Autoencoders, and further get familiar with the advanced concepts of Natural Language Processing. Also, gain practical exposure on text summarization and processing. Our cloud

Deep Learning with Python TrainingTraining Key Features

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  • Who is Python Deep Learning Course for? Data Engineers Data Analyst Data Scientist Machine Learning Engineers Anyone who wants to add Deep Learning with TensorFlow skills to their profile Teams getting started on Deep Learning with TensorFlow projects Anyone who wants to understand the Deep Neural Networks
Skills Covered
  • What are the prerequisites for Python Deep Learning Course? Working Knowledge in Python Understanding of Machine Learning Models – Regression and Classification Working Knowledge of Python Machine Learning Module (scikit-learn)
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Deep Learning with Python Training Course Curriculum

Benefits

At the end of Deep Learning with Python training participants will be able to: Understand core architecture of Deep Neural Networks Use TensorFlow and Keras Construct a computing environment and learn to install TensorFlow Develop TensorFlow graphs required for everyday computation

Pre-requisites

past 25 years developing and researching cutting-edge artificial intelligent systems. He has (co)founded several companies, advises high-tech startups and held appointments at AT&T (Executive Director of Research), Turn Inc., Xerox Research, Mitsubishi Research, and at Clairvoyance Corp. He teaches at UC Berkeley and has published six books, more than 50 research publications, and has over 20 patents in the areas of machine learning and information processing.

Course Content

  • Artificial Intelligence - Fundamentals
    • test 1
  • Machine Learning - Fundamentals

  • Branding
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